CN108811069A - A kind of Poewr control method of the full duplex non-orthogonal multiple access system based on efficiency - Google Patents
A kind of Poewr control method of the full duplex non-orthogonal multiple access system based on efficiency Download PDFInfo
- Publication number
- CN108811069A CN108811069A CN201810982276.2A CN201810982276A CN108811069A CN 108811069 A CN108811069 A CN 108811069A CN 201810982276 A CN201810982276 A CN 201810982276A CN 108811069 A CN108811069 A CN 108811069A
- Authority
- CN
- China
- Prior art keywords
- user
- base station
- downlink user
- uplink user
- indicate
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W52/00—Power management, e.g. TPC [Transmission Power Control], power saving or power classes
- H04W52/04—TPC
- H04W52/30—TPC using constraints in the total amount of available transmission power
- H04W52/34—TPC management, i.e. sharing limited amount of power among users or channels or data types, e.g. cell loading
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W52/00—Power management, e.g. TPC [Transmission Power Control], power saving or power classes
- H04W52/04—TPC
- H04W52/06—TPC algorithms
- H04W52/14—Separate analysis of uplink or downlink
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W52/00—Power management, e.g. TPC [Transmission Power Control], power saving or power classes
- H04W52/04—TPC
- H04W52/18—TPC being performed according to specific parameters
- H04W52/24—TPC being performed according to specific parameters using SIR [Signal to Interference Ratio] or other wireless path parameters
- H04W52/243—TPC being performed according to specific parameters using SIR [Signal to Interference Ratio] or other wireless path parameters taking into account interferences
Landscapes
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Mobile Radio Communication Systems (AREA)
Abstract
A kind of Poewr control method of the full duplex non-orthogonal multiple access system based on efficiency of the present invention, belong to network power control field, Optimized model is established for the efficiency problem of single carrier non-orthogonal multiple system that full duplex base station provides service for multiple half-duplex downlink users and uplink user simultaneously is used, then fractional programming and the iterative algorithm based on Lagrange multiplier is used to be allocated transmission power, to realize that system energy efficiency maximizes.The invention acquired results improve the energy efficiency of full duplex NOMA systems, to a certain extent, reduce computation complexity.
Description
Technical field
The invention belongs in non-orthogonal multiple access communications field, band in especially a kind of full duplex non-orthogonal multiple access
There is the Poewr control method based on efficiency of service quality guarantee.
Background technology
In the novel multiple access technology researchs of newest 5G, the non-orthogonal multiple access technology based on power domain multiplexing is 5G nets
Power system capacity is improved in network, improves frequency effect, a kind of technology having wide application prospects of efficiency.NOMA technologies are relative to traditional
OMA technologies have the following advantages that：Higher spectrum efficiency, higher cell edge throughput, more low transmission stand-by period, enhancing
User fairness connects number etc. with the more users of support.
However, most of work of NOMA so far is only limitted to either-way operation.All due to NOMA and full duplex technology
Improve spectrum efficiency.Potential application of the full-duplex transceiver in NOMA systems is to allow to be carried out at the same time in cellular networks
Line link and downlink transmission, wherein in uplink channel pairing user data and downlink channel in
Pairing user data the same time on a same frequency.It newest is ground about what full-duplex operation and NOMA principles were combined
Study carefully seldom, currently, by finding that existing achievement in research is concentrated mainly on lower section to cooperation NOMA systematic research Analysis on Results
Face.As Sun Y et al. exist《IEEE Communications Letters,2017,65(3):1077-1091》On deliver it is entitled
“Optimal joint power and subcarrier allocation for full-duplex
The article of multicarriernon-orthogonal multiple access systems " is to be based on full duplex NOMA systems
The weighted sum capacity of system proposes the optimal and suboptimum power allocation scheme of NOMA.Secondly, it is the property traversed for system with rate
It can study, as Zhang C et al. exist《IEEE Communications Letters,2016,22:2478-2481.》On deliver
" Non-orthogonal multiple access with cooperative full-duplex relaying " text
Chapter is the power allocation scheme that traversal and rate based on full duplex cooperation NOMA relay systems propose NOMA.
Therefore, for full duplex NOMA systems, it is concentrated mainly on the power consumption of optimization system, power system capacity and with rate etc.
Performance indicator, few energy efficiencies to system are studied.It is necessary to consider that research is based on most in full duplex NOMA systems
The resource allocation methods of bigization efficiency.
Invention content
Present invention seek to address that the above problem of the prior art.Propose a kind of energy efficiency improving system, practicality
Property and feasibility it is strong full duplex non-orthogonal multiple access the Poewr control method based on efficiency.Technical scheme of the present invention is such as
Under：
A kind of Poewr control method of the full duplex non-orthogonal multiple access system based on efficiency comprising following steps：
In full duplex non-orthogonal multiple access system, defining efficiency optimization problem is：It realizes and maximizes NOMA communication systems
The guarantee simultaneously of the energy efficiency of system includes the service quality of uplink user and downlink user, by using control uplink user and base
The optimization problem is described as problem P1 by the method for the transmission power stood：
Problem P1 is converted to fractional programming problems and subtracts formula form, and defined function F (x)=f (pk,qj)-xg(pk,
qj) equally convert optimization problem P1 to optimization problem P2：WhereinExpression system
And rate summation,The total power consumption of expression system.
Solve problems P2 is equivalent to solve F (x*)=0, whereinThen optimization problem P2 is equivalent to optimize
Problem P3：
P3：
Introduce multiplier λ and μk, it is deformed into subproblem P4：
In order to solve optimal solution (pk *, qj *) thought of layering is used to optimize solution to problem P4.
Further, the optimization problem P1 is：
P1:
Wherein：
It is confined to：
In problem P1, each parameter definition is as follows：
RUL：In expression system uplink user and rate；
RDL：In expression system downlink user and rate；
pc：Circuit loss in expression system；
pk：Distribute to the transmission power of downlink user k in base station；
qj：The transmission power of uplink user j；
Indicate the path loss between downlink user k and base station and shadow fading；
Indicate the path loss between uplink user j and base station and shadow fading；
Indicate the path loss between uplink user j and downlink user k and shadow fading；
The maximum power summation of Base Transmitter to downlink user limits；
The maximum transmission power limitation of single uplink user；
hk：Base station is to the channel gain between downlink user k links, without loss of generality, enable 0≤| h1|≤|h2|≤…≤|hK
|；
gj：Uplink user j is to the channel gain between base station link, without loss of generality, enables | g1|≥|g2|≥...≥|gJ|
≥0；
fj,k：Uplink user j is to the channel gain between downlink user k links；
Indicate the white Gaussian noise at downlink user k；
Indicate the white Gaussian noise of base station；
Γk：The throughput demands of downlink user k；
The throughput demands of uplink user j；
lSI：Base station self-interference channel gain；
ρ：0 < ρ < < 1 indicate a constant of self-interference eradicating efficacy.
Further, described be converted to problem P1 with fractional programming problems subtracts formula form, and defined function F (x)=f
(pk,qj)-xg(pk,qj) equally convert optimization problem P1 to optimization problem P2, it specifically includes：Definition
P2:
It is limited to：
F(x)≥0,
Wherein x is auxiliary variable；
Further, the Solve problems P2 is equivalent to solve F (x*)=0, whereinThen optimization is asked
Topic P2 is equivalent to optimization problem P3：It specifically includes：
P3：
It is limited to：
WhereinThen pk *,qj *For the optimal solution of problem P3.
Further, introducing the multiplier λ and μk, it is deformed into subproblem P4, is specifically included：
For Solve problems P3, enable Introduce multiplier λ and μk, become
Shape is following subproblem P4：
P4-A：
P4-B：
Further, described in order to solve optimal solution (pk *, qj *) problem P4 is optimized using the thought of layering and is asked
Solution, step are：
Step 4.1：Initialize outer layer maximum iteration lmaxWith maximum terminal error ε, l=0 and x=0 are enabled first；
Step 4.2：Initialize internal layer maximum iteration tmaxWith multiplier α, βk,ηj,μk, λ, and enable t=0.According to
Given x can obtain optimal solution (p by step (4)k *, qj *)：
Step 4.3：Lagrange multiplier α, β are updated according to Subgradient Algorithmk,ηj,μk, λ, and t+1 is assigned to t.
Until internal layer iteration convergence or t=tmax, and return to optimal solution (pk *,qj *)；
Step 4.4：Optimal solution (the p obtained according to above-mentioned steps 4.3k *,qj *), to judge f (pk *,qj*)-xg(pk *,qj *)
< ε are then returned if it is determined that not restrainingOtherwise it does not restrain, enablesAnd it returns
Step 4.2 is returned, until external iteration convergence or l=lmax, then terminating algorithm.
It advantages of the present invention and has the beneficial effect that：
The present invention is directed to the efficiency maximization problems based on full duplex NOMA systems, is meeting each user's minimum data speed
In the case that rate constrains, using fractional programming and Lagrange duality method, proposes a kind of power control scheme, maximize system
Energy efficiency.Method provided by the present invention compares other schemes and (is based on NOMA maximum power transmission schemes MPT-NOMA
And traditional OMA schemes) energy efficiency of system is improved, practicability and feasibility are strong.
Description of the drawings
Fig. 1 is the system model that the present invention provides the full duplex NOMA networks that preferred embodiment provides；
Fig. 2 is that the present invention compares influence of the different self-interference elimination amounts to system energy efficiency.
Fig. 3 is the base station maximum transmission power of present invention comparison algorithm (carried NOMA schemes, tradition OMA schemes) to system
The influence of efficiency.
The flow diagram of Fig. 4 present invention.
Specific implementation mode
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, detailed
Carefully describe.Described embodiment is only a part of the embodiment of the present invention.
The present invention solve above-mentioned technical problem technical solution be：
Technical scheme is as follows：
(1) in full duplex non-orthogonal multiple access system, defining efficiency optimization problem is：It realizes and maximizes NOMA communications
The energy efficiency of system ensure simultaneously include uplink user and downlink user service quality, by using control uplink user with
The optimization problem is described as problem P1 by the method for the transmission power of base station：
P1:
Wherein：
It is confined to：
In problem P1, each parameter definition is as follows：
pk：Distribute to the transmission power of downlink user k in base station；
qj：The transmission power of uplink user j；
Indicate the path loss between downlink user k and base station and shadow fading；
Indicate the path loss between uplink user j and base station and shadow fading；
Indicate the path loss between uplink user j and downlink user k and shadow fading；
The maximum power summation of Base Transmitter to downlink user limits；
The maximum transmission power limitation of single uplink user；
hk：Base station is to the channel gain between downlink user k links, without loss of generality, enable 0≤| h1|≤|h2|≤…≤|hK
|；
gj：Uplink user j is to the channel gain between base station link, without loss of generality, enables | g1|≥|g2|≥...≥|gJ|
≥0；
fj,k：Uplink user j is to the channel gain between downlink user k links；
Indicate the white Gaussian noise at downlink user k；
Indicate the white Gaussian noise of base station；
Γk：The throughput demands of downlink user k；
The throughput demands of uplink user j；
lSI：Base station self-interference channel gain；
ρ：0 < ρ < < 1 indicate a constant of self-interference eradicating efficacy.
(2) it definesProblem P1 is transported
It is converted to fractional programming problems and subtracts formula form, and defined function F (x)=f (pk,qj)-xg(pk,qj) by optimization problem P1 etc.
It is converted into optimization problem P2 to effect：
P2:
It is limited to：
F(x)≥0,
It is asking
It inscribes in P2, each parameter definition is as follows：
pk：Distribute to the transmission power of downlink user k in base station；
qj：The transmission power of uplink user j；
Indicate the path loss between downlink user k and base station and shadow fading；
Indicate the path loss between uplink user j and base station and shadow fading；
Indicate the path loss between uplink user j and downlink user k and shadow fading；
The maximum power summation of Base Transmitter to downlink user limits；
The maximum transmission power limitation of single uplink user；
hk：Base station is to the channel gain between downlink user k links, without loss of generality, enable 0≤| h1|≤|h2|≤…≤|hK
|；
gj：Uplink user j is to the channel gain between base station link, without loss of generality, enables | g1|≥|g2|≥...≥|gJ|
≥0；
fj,k：Uplink user j is to the channel gain between downlink user k links；
Indicate the white Gaussian noise at downlink user k；
Indicate the white Gaussian noise of base station；
Γk：The throughput demands of downlink user k；
Υj：The throughput demands of uplink user j；
lSI：Base station self-interference channel gain；
ρ：0 < ρ < < 1 indicate a constant of self-interference eradicating efficacy；
Ak：
Bj：
x：Assist control variable to be determined；
(3) Solve problems P2 is equivalent to solve F (x*)=0, whereinThen optimization problem P2 is equivalent to
Optimization problem P3：
P3：
It is limited to：
Then
pk *,qj *For the optimal solution of problem P3
(4) it is Solve problems P3, enables Introduce multiplier λ and
μk, it is deformed into following subproblem P4：
P4-A：
It is limited to：
The Lagrangian of the above problem is defined as：
Wherein, α, βk,ηj,μk, the corresponding Lagrange multiplier of each constraints of λ expressions.Then Lagrangian
Dual problem of equal value is：
P4-B：
By to the q in problem P4-Bj,pk,fk, S asks local derviation that can obtain respectively：
pk *, qj *The respectively optimal power allocation of downlink user k and uplink user j.
Following Lagrange multiplier is updated using Subgradient Algorithm：
Wherein,It is base station maximum transmission power,It is the maximum transmission power of single uplink, t indicates that iteration refers to
Number, ξi(i=1,2,3,4,5,6) indicates newer step-length, AkAnd BjUplink user k respectively with downlink user j about user most
The expression formula of low rate demand.
In order to solve optimal solution (pk *, qj *) thought of layering is used to optimize solution to problem P4, step is：
Step 4.1：Initialize outer layer maximum iteration lmaxWith maximum terminal error ε, l=0 and x=0 are enabled first；
Step 4.2：Initialize internal layer maximum iteration tmaxWith multiplier α, βk,ηj,μk,λ.And enable t=0.According to
Given x can obtain optimal solution (p by step (4)k *, qj *)：
Step 4.3：Lagrange multiplier α, β are updated according to Subgradient Algorithmk,ηj,μk, λ, and t+1 is assigned to t.
Until internal layer iteration convergence or t=tmax, and return to optimal solution (pk *,qj *)；
Step 4.4：Optimal solution (the p obtained according to above-mentioned steps 4.3k *,qj *), to judge f (pk *,qj*)-xg(pk *,qj *)
< ε are then returned if it is determined that not restrainingOtherwise it does not restrain, enablesAnd it returns
Step 4.2 is returned, until external iteration convergence or l=lmax, then terminating algorithm.
The present invention discloses the resource allocation algorithm of full duplex NOMA system powers distribution, including：External iteration is initial first
Change maximum iteration lmaxWith maximum decision threshold ε；And setting initial maximum efficiency x=0 and iteration index l=0；Then it gives
A fixed x solves resource allocation problem to obtain resource allocation policy；Efficiency updates convergent judgement, calculates newer efficiency
Value, if the difference of newer efficiency and the efficiency of last time is not more than maximum decision threshold, efficiency convergence provides maximum efficiency
Value, method terminate；It, will new calculated energy if the difference of newer efficiency and the efficiency of last time is more than maximum decision threshold
Valid value saves as energy valid value at this time, and goes to more newly assigned power in third step, until efficiency convergence or iterations reach
To lmax, provide maximum efficiency.
And internal layer iteration initialization iteration index t=0 and maximum iteration tmax；And Lagrange multiplier α is initialized,
βk,ηj,μk, λ and resource allocation policy { pk,qj(working as t=0)；Solve the power distribution of uplink user k and downlink user j
pk、qj；Using subgradient method update Lagrange multiplier α, βk,ηj,μk,λ；Until convergence or iterations reach tmax。
The present embodiment is the resource allocation algorithm of cooperation NOMA system combined power distribution and gain amplifier selection, at one
Cooperate NOMA networks in, it is contemplated that cell in there are one base station, K downlink user and J uplink user random distribution outside
In the annulus that radius is 600 meters and inside radius is 30 meters, minimum data rate Rk min=0.5bit/s/Hz, base station maximum transmission
Power Pmax=35dBm, uplink user maximum transmission powerCircuit constant power dissipation Pc=20dBm, path loss
Index is 3.6, system bandwidth 5MHz, and self-interference eliminates constant ρ=- 110dBm, downlink user noise power and base station noise
Power is respectively：
In the present embodiment, Fig. 1 is that the present invention provides system model in full duplex NOMA networks, a base station in figure, K
A downlink user and J uplink user, in downlink, full duplex base station gives downlink user to send information；In uplink, on
Row user sends a signal to uplink user.Wherein downlink user receives the interference of uplink user and the self-interference of base station.Fig. 2
It is influence relationship comparison diagram of the different self-interference elimination amounts of comparison to system energy efficiency；Fig. 3 is in the power distribution sides NOMA proposed
In case, traditional OMA schemes the efficiency comparison diagram of system is obtained with base station maximum transmission changed power；As can be seen from Figure 2
As self-interference eliminates the increase of constant, the system efficiency that is averaged shows the trend of monotone decreasing.This is because bigger is certainly dry
More residual interferences can be led in base station by disturbing elimination constant.From figure 3, it can be seen that NOMA schemes and tradition OMA schemes
Efficiency is all with PmaxGrowth and increase, and work as PmaxEfficiency is not just further added by after reaching certain value, this is because transmission power
pkAnd qjThe efficiency highest for the realization for having reached optimal value, but having been suggested plans.
The above embodiment is interpreted as being merely to illustrate the present invention rather than limit the scope of the invention.?
After the content for having read the record of the present invention, technical staff can make various changes or modifications the present invention, these equivalent changes
Change and modification equally falls into the scope of the claims in the present invention.
Claims (6)
1. a kind of Poewr control method of the full duplex non-orthogonal multiple access system based on efficiency, which is characterized in that including following
Step：
In full duplex non-orthogonal multiple access system, defining efficiency optimization problem is：It realizes and maximizes NOMA communication systems
Energy efficiency ensure simultaneously include uplink user and downlink user service quality, by using controlling uplink user and base station
The optimization problem is described as problem P1 by the method for transmission power：
Problem P1 is converted to fractional programming problems and subtracts formula form, and defined function F (x)=f (pk,qj)-xg(pk,qj) will
Optimization problem P1 is equally converted into optimization problem P2：WhereinExpression system
And rate,The total power consumption of expression system；
Solve problems P2 is equivalent to solve F (x*)=0, whereinThen optimization problem P2 is equivalent to optimization problem
P3：
P3：
Introduce multiplier λ and μk, it is deformed into subproblem P4：
In order to solve optimal solution (pk *, qj *) thought of layering is used to optimize solution to problem P4.
2. a kind of Poewr control method of the full duplex non-orthogonal multiple access system based on efficiency according to claim 1,
It is characterized in that, the optimization problem P1 is：
P1:
Wherein：
It is confined to：
In problem P1, each parameter definition is as follows：
RUL：In expression system uplink user and rate；
RDL：In expression system downlink user and rate；
pc：Circuit loss in expression system；
pk：Distribute to the transmission power of downlink user k in base station；
qj：The transmission power of uplink user j；
Indicate the path loss between downlink user k and base station and shadow fading；
Indicate the path loss between uplink user j and base station and shadow fading；
θj,k：Indicate the path loss between uplink user j and downlink user k and shadow fading；
The maximum power summation of Base Transmitter to downlink user limits；
The maximum transmission power limitation of single uplink user；
hk：Base station is to the channel gain between downlink user k links, without loss of generality, enable 0≤| h1|≤|h2|≤…≤|hK|；
gj：Uplink user j is to the channel gain between base station link, without loss of generality, enables | g1|≥|g2|≥...≥|gJ|≥0；
fj,k：Uplink user j is to the channel gain between downlink user k links；
Indicate the white Gaussian noise at downlink user k；
Indicate the white Gaussian noise of base station；
Γk：The throughput demands of downlink user k；
Υj：The throughput demands of uplink user j；
lSI：Base station self-interference channel gain；
ρ：0 < ρ < < 1 indicate a constant of self-interference eradicating efficacy.
3. a kind of Poewr control method of the full duplex non-orthogonal multiple access system based on efficiency according to claim 2,
It is characterized in that, passing through definition Problem P1 is transported
It is converted to fractional programming problems and subtracts formula form, and defined function F (x)=f (pk,qj)-xg(pk,qj), wherein by optimization problem
P1 is equally converted into optimization problem P2：
P2:
It is limited to：
F(x)≥0,
In problem P2, each parameter definition is as follows：
pk：Distribute to the transmission power of downlink user k in base station；
qj：The transmission power of uplink user j；
Indicate the path loss between downlink user k and base station and shadow fading；
Indicate the path loss between uplink user j and base station and shadow fading；
θj,k：Indicate the path loss between uplink user j and downlink user k and shadow fading；
The maximum power summation of Base Transmitter to downlink user limits；
The maximum transmission power limitation of single uplink user；
hk：Base station is to the channel gain between downlink user k links, without loss of generality, enable 0≤| h1|≤|h2|≤…≤|hK|；
gj：Uplink user j is to the channel gain between base station link, without loss of generality, enables | g1|≥|g2|≥...≥|gJ|≥0；
fj,k：Uplink user j is to the channel gain between downlink user k links；
Indicate the white Gaussian noise at downlink user k；
Indicate the white Gaussian noise of base station；
Γk：The throughput demands of downlink user k；
Υj：The throughput demands of uplink user j；
lSI：Base station self-interference channel gain；
ρ：0 < ρ < < 1 indicate a constant of self-interference eradicating efficacy；
Ak：
Bj：
x：Assist control variable to be determined.
4. a kind of Poewr control method of the full duplex non-orthogonal multiple access system based on efficiency according to claim 3,
It is characterized in that, the Solve problems P2, is equivalent to solve F (x*)=0, whereinThen optimization problem P2 etc.
Valence is optimization problem P3：
P3：
It is limited to：
WhereinThen pk *,qj *For the optimal solution of problem P3.
5. a kind of Poewr control method of the full duplex non-orthogonal multiple access system based on efficiency according to claim 4,
It is characterized in that, introducing the multiplier λ and μk, it is deformed into subproblem P4, is specifically included：
For Solve problems P3, enableIntroduce multiplier λ and μk, it is deformed into
Following subproblem P4：
P4-A：
It is limited to：
The Lagrangian of the above problem is defined as：
Wherein, α, βk,ηj,μk, the corresponding Lagrange multiplier of each constraints of λ expressions.Then Lagrangian is of equal value
Dual problem is：
P4-B：
By to the q in problem P4-Bj,pk,fk, S asks local derviation that can obtain respectively：
pk *, qj *The respectively optimal power allocation of downlink user k and uplink user j；
Following Lagrange multiplier is updated using Subgradient Algorithm：
Wherein,It is base station maximum transmission power,It is the maximum transmission power of single uplink, t indicates iteration index, ξi(i
=1,2,3,4,5,6) newer step-length, A are indicatedkAnd BjIt is uplink user k respectively with downlink user j about user's minimum speed limit
The expression formula of demand.
6. a kind of Poewr control method of the full duplex non-orthogonal multiple access system based on efficiency according to claim 4,
It is characterized in that, described in order to solve optimal solution (pk *,qj *) thought of layering is used to optimize solution, step to problem P4
For：
Step 4.1：Initialize outer layer maximum iteration lmaxWith maximum terminal error ε, l=0 and x=0 are enabled first；
Step 4.2：Initialize internal layer maximum iteration tmaxWith multiplier α, βk,ηj,μk, λ, and enable t=0.According to given
X, optimal solution (p can be obtained by step (4)k *, qj *)：
Step 4.3：Lagrange multiplier α, β are updated according to Subgradient Algorithmk,ηj,μk, λ, and t+1 is assigned to t.Until interior
Layer iteration convergence or t=tmax, and return to optimal solution (pk *,qj *)；
Step 4.4：Optimal solution (the p obtained according to above-mentioned steps 4.3k *,qj *), to judge f (pk *,qj*)-xg(pk *,qj *) < ε,
If it is determined that not restraining, then returnOtherwise it does not restrain, enablesAnd return to step
Rapid 4.2, until external iteration convergence or l=lmax, then terminating algorithm.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810982276.2A CN108811069B (en) | 2018-08-27 | 2018-08-27 | Energy efficiency-based power control method for full-duplex non-orthogonal multiple access system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810982276.2A CN108811069B (en) | 2018-08-27 | 2018-08-27 | Energy efficiency-based power control method for full-duplex non-orthogonal multiple access system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN108811069A true CN108811069A (en) | 2018-11-13 |
| CN108811069B CN108811069B (en) | 2021-07-13 |
Family
ID=64080799
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810982276.2A Active CN108811069B (en) | 2018-08-27 | 2018-08-27 | Energy efficiency-based power control method for full-duplex non-orthogonal multiple access system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108811069B (en) |
Cited By (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109769292A (en) * | 2019-01-31 | 2019-05-17 | 哈尔滨工业大学（深圳） | Resource allocation methods, system, equipment and computer media |
| CN110113809A (en) * | 2019-04-28 | 2019-08-09 | 北京邮电大学 | Disturbance restraining method based on power control and transmission direction selection |
| CN110191476A (en) * | 2019-04-18 | 2019-08-30 | 浙江大学 | A kind of non-orthogonal multiple cut-in method based on reconfigurable antenna array |
| CN110299937A (en) * | 2019-07-24 | 2019-10-01 | 南京邮电大学 | A kind of Uplink MIMO-NOMA wireless communication system beam-forming method |
| CN110505028A (en) * | 2019-08-22 | 2019-11-26 | 河南理工大学 | The power distribution method of maximum energy efficiency in uplink NOMA system |
| CN111200813A (en) * | 2019-11-22 | 2020-05-26 | 重庆邮电大学 | Large-scale MIMO system maximized minimum user safety energy efficiency optimization method based on SWIPT |
| CN111726156A (en) * | 2020-06-06 | 2020-09-29 | 郑州大学 | NOMA-based resource allocation method and device |
| CN111866061A (en) * | 2020-06-02 | 2020-10-30 | 浙江工业大学 | Mobile edge computing time delay optimization method based on non-orthogonal multiple access and cellular network user cooperation |
| CN112291841A (en) * | 2020-10-24 | 2021-01-29 | 中国人民解放军国防科技大学 | User cooperation method based on backscattering under power domain non-orthogonal multiple access |
| CN112333813A (en) * | 2020-11-03 | 2021-02-05 | 重庆邮电大学 | Cooperative NOMA network maximization and rate power distribution method under hardware damage |
| WO2021120962A1 (en) * | 2019-12-16 | 2021-06-24 | 中国科学院深圳先进技术研究院 | Hierarchical multiple access method for environmental backscatter network |
| CN113543145A (en) * | 2021-06-07 | 2021-10-22 | 北京邮电大学 | NOMA system user pairing and power distribution joint optimization method and device |
| CN113923767B (en) * | 2021-09-23 | 2023-10-13 | 怀化建南电子科技有限公司 | Energy efficiency maximization method for multi-carrier cooperation non-orthogonal multiple access system |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104640220A (en) * | 2015-03-12 | 2015-05-20 | 重庆邮电大学 | Frequency and power distributing method based on NOMA (non-orthogonal multiple access) system |
| CN105554790A (en) * | 2016-01-20 | 2016-05-04 | 西安电子科技大学 | Energy efficiency optimization method in asymmetric bidirectional relay system |
| US20170223695A1 (en) * | 2016-02-03 | 2017-08-03 | Lg Electronics Inc. | Method and apparatus for transmitting an uplink channel in a wireless communication system |
| CN107105492A (en) * | 2017-05-04 | 2017-08-29 | 桂林电子科技大学 | The method for improving ultra dense heterogeneous network energy efficiency is accessed based on non-orthogonal multiple |
| CN107148078A (en) * | 2017-04-18 | 2017-09-08 | 浙江大学 | A kind of user access control method and device for mixing full duplex half-duplex network |
| CN108235419A (en) * | 2018-01-16 | 2018-06-29 | 重庆邮电大学 | Poewr control method based on SWIPT in isomery cellular network |
-
2018
- 2018-08-27 CN CN201810982276.2A patent/CN108811069B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104640220A (en) * | 2015-03-12 | 2015-05-20 | 重庆邮电大学 | Frequency and power distributing method based on NOMA (non-orthogonal multiple access) system |
| CN105554790A (en) * | 2016-01-20 | 2016-05-04 | 西安电子科技大学 | Energy efficiency optimization method in asymmetric bidirectional relay system |
| US20170223695A1 (en) * | 2016-02-03 | 2017-08-03 | Lg Electronics Inc. | Method and apparatus for transmitting an uplink channel in a wireless communication system |
| CN107148078A (en) * | 2017-04-18 | 2017-09-08 | 浙江大学 | A kind of user access control method and device for mixing full duplex half-duplex network |
| CN107105492A (en) * | 2017-05-04 | 2017-08-29 | 桂林电子科技大学 | The method for improving ultra dense heterogeneous network energy efficiency is accessed based on non-orthogonal multiple |
| CN108235419A (en) * | 2018-01-16 | 2018-06-29 | 重庆邮电大学 | Poewr control method based on SWIPT in isomery cellular network |
Non-Patent Citations (2)
| Title |
|---|
| ANKIT GUPTA等: "An Energy-Efficient Approach Towards Power Allocation in Non-Orthogonal Multiple Access Full-Duplex AF Relay Systems", 《2018 IEEE 19TH INTERNATIONAL WORKSHOP ON SIGNAL PROCESSING ADVANCES IN WIRELESS COMMUNICATIONS (SPAWC)》 * |
| 王正强等: "非正交多址系统资源分配研究综述", 《电信科学》 * |
Cited By (17)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109769292A (en) * | 2019-01-31 | 2019-05-17 | 哈尔滨工业大学（深圳） | Resource allocation methods, system, equipment and computer media |
| CN110191476A (en) * | 2019-04-18 | 2019-08-30 | 浙江大学 | A kind of non-orthogonal multiple cut-in method based on reconfigurable antenna array |
| CN110191476B (en) * | 2019-04-18 | 2020-07-14 | 浙江大学 | Reconfigurable antenna array-based non-orthogonal multiple access method |
| CN110113809A (en) * | 2019-04-28 | 2019-08-09 | 北京邮电大学 | Disturbance restraining method based on power control and transmission direction selection |
| CN110113809B (en) * | 2019-04-28 | 2021-01-29 | 北京邮电大学 | Interference suppression method based on power control and transmission direction selection |
| CN110299937A (en) * | 2019-07-24 | 2019-10-01 | 南京邮电大学 | A kind of Uplink MIMO-NOMA wireless communication system beam-forming method |
| CN110505028A (en) * | 2019-08-22 | 2019-11-26 | 河南理工大学 | The power distribution method of maximum energy efficiency in uplink NOMA system |
| CN110505028B (en) * | 2019-08-22 | 2022-02-08 | 河南理工大学 | Power distribution method for maximizing energy efficiency in uplink NOMA system |
| CN111200813A (en) * | 2019-11-22 | 2020-05-26 | 重庆邮电大学 | Large-scale MIMO system maximized minimum user safety energy efficiency optimization method based on SWIPT |
| CN111200813B (en) * | 2019-11-22 | 2022-03-22 | 重庆邮电大学 | Large-scale MIMO system maximized minimum user safety energy efficiency optimization method based on SWIPT |
| WO2021120962A1 (en) * | 2019-12-16 | 2021-06-24 | 中国科学院深圳先进技术研究院 | Hierarchical multiple access method for environmental backscatter network |
| CN111866061A (en) * | 2020-06-02 | 2020-10-30 | 浙江工业大学 | Mobile edge computing time delay optimization method based on non-orthogonal multiple access and cellular network user cooperation |
| CN111726156A (en) * | 2020-06-06 | 2020-09-29 | 郑州大学 | NOMA-based resource allocation method and device |
| CN112291841A (en) * | 2020-10-24 | 2021-01-29 | 中国人民解放军国防科技大学 | User cooperation method based on backscattering under power domain non-orthogonal multiple access |
| CN112333813A (en) * | 2020-11-03 | 2021-02-05 | 重庆邮电大学 | Cooperative NOMA network maximization and rate power distribution method under hardware damage |
| CN113543145A (en) * | 2021-06-07 | 2021-10-22 | 北京邮电大学 | NOMA system user pairing and power distribution joint optimization method and device |
| CN113923767B (en) * | 2021-09-23 | 2023-10-13 | 怀化建南电子科技有限公司 | Energy efficiency maximization method for multi-carrier cooperation non-orthogonal multiple access system |
Also Published As
| Publication number | Publication date |
|---|---|
| CN108811069B (en) | 2021-07-13 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108811069A (en) | A kind of Poewr control method of the full duplex non-orthogonal multiple access system based on efficiency | |
| Khan et al. | Efficient power allocation in downlink multi‐cell multi‐user NOMA networks | |
| Zhang et al. | Energy efficient resource allocation in terahertz downlink NOMA systems | |
| Han et al. | Distance-aware bandwidth-adaptive resource allocation for wireless systems in the terahertz band | |
| He et al. | Energy-efficient resource allocation in OFDM systems with distributed antennas | |
| Cheung et al. | Achieving maximum energy-efficiency in multi-relay OFDMA cellular networks: A fractional programming approach | |
| Fang et al. | Energy efficiency of resource scheduling for non-orthogonal multiple access (NOMA) wireless network | |
| CN108848563B (en) | Energy-efficiency-based resource allocation method for downlink of cooperative NOMA (non-orthogonal multiple access) system | |
| CN108601087B (en) | Wireless communication resource allocation method based on network slice | |
| CN107613556B (en) | Full-duplex D2D interference management method based on power control | |
| Shim et al. | Fairness-aware resource allocation in a cooperative OFDMA uplink system | |
| Jing et al. | Flexible resource allocation for joint optimization of energy and spectral efficiency in OFDMA multi-cell networks | |
| Su et al. | Joint location and beamforming optimization for STAR-RIS aided NOMA-UAV networks | |
| CN109362090A (en) | Recognize the maximized power distribution optimization method of junction network energy efficiency | |
| Yassin et al. | Cooperative resource management and power allocation for multiuser OFDMA networks | |
| Liu et al. | Energy efficient resource allocation based on relay selection and subcarrier pairing with channel uncertainty in cognitive radio network | |
| CN107276704A (en) | The maximized optimal robustness Poewr control method of efficiency is based in two layers of Femtocell network | |
| Wang et al. | Power allocation for D2D aided cooperative NOMA system with imperfect CSI | |
| Al-Wesabi et al. | Optimal resource allocation method for device-to-device communication in 5g networks | |
| Cheung et al. | Maximizing energy-efficiency in multi-relay OFDMA cellular networks | |
| Gao et al. | Stackelberg game-based energy efficient power allocation for heterogeneous NOMA networks | |
| Lei et al. | Power and discrete rate adaptation in BER constrained wireless powered communication networks | |
| CN103491620B (en) | Based on the distributed uplink power control method of user-driven in a kind of heterogeneous network | |
| Zhang et al. | End-to-end outage minimization in OFDM based linear relay networks | |
| CN114520989A (en) | Multi-carrier digital energy simultaneous transmission NOMA network energy efficiency maximization method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |